文章基本信息

标题：Using Sentiment Analysis for Stock Exchange Prediction
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作者：Milson L.Lima ; Thiago P. Nascimento ; Sofiane Labidi 等
期刊名称：International Journal of Artificial Intelligence & Applications (IJAIA)
印刷版ISSN：0976-2191
电子版ISSN：0975-900X
出版年度：2016
卷号：7
期号：1
页码：59
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The economic growth is a consensus in any country. To grow economically, it is necessary to channel therevenues for investment. One way of raising is the capital market and the stock exchanges. In this context,predicting the behavior of shares in the stock exchange is not a simple task, as itinvolvesvariables not always known and can undergo various influences, from the collective emotion tohigh-profile news. Such volatility can represent considerable financial losses for investors. Inorder to anticipate such changes in the market, it has been proposed various mechanisms tryingto predict the behavior of an asset in the stock market, based on previously existing information.Such mechanisms include statistical data only, without considering the collective feeling. Thispaper is going to use natural language processing algorithms (LPN) to determine thecollective mood on assets and later with the help of the SVM algorithm to extract patterns in anattempt to predict the active behaviour.
关键词：Sentiment Analysis; Machine Learning; Stock Exchange; Petrobras; Artificial Intelligence